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CBQ: Cross-Block Quantization for Large Language Models
Post-training quantization (PTQ) has played a key role in compressing large language models (LLMs) with ultra-low costs.
Advanced Efficient Strategy for Detection of Dark Objects Based on Spiking Network with Multi-Box Detection
The whole study proposes a combination of spiked and normal convolution layers as an energy-efficient and reliable object detector model.
Boosting Mobile CNN Inference through Semantic Memory
Human brains are known to be capable of speeding up visual recognition of repeatedly presented objects through faster memory encoding and accessing procedures on activated neurons.
Weight-dependent Gates for Network Pruning
In this paper, a simple yet effective network pruning framework is proposed to simultaneously address the problems of pruning indicator, pruning ratio, and efficiency constraint.
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